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Investigating Novel Coronavirus Through Statistical Methods for Biomedical Applications: An Engineering Student Perspective
International Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2021 ; 841:341-347, 2022.
Article in English | Scopus | ID: covidwho-1787772
ABSTRACT
The World of today is suffering from novel coronavirus (nCOV2). This is a respiratory infectious disease that has affected the entire globe. This respiratory infection is first originated in Wuhan, China. Today, it has many variants like the “United Kingdom (UK) variant called B.1.1.7,” “South African variant is called B.1.351,” “Brazilian variant is known as P.1,” etc. In this research work, we will discuss the Indian scenario to tackle nCOV2. We will also present an engineering student’s perspective to detect changes developed in the patient’s chest suffering from nCOV2 employing statistical methods. Among all the statistical techniques, GLCM-based texture analysis-based technique has gained popularity due to its diverse applications. It is used in many applications like remote sensing, image processing, biomedical applications, seismic data analysis. Thus in this research work, this methodology is used various changes in the before and after images of the patient suffering from the novel coronavirus. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: International Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: International Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2021 Year: 2022 Document Type: Article